Skip to content

Category

edge computing

2,462 papers

#graph neural networks Open access Sep 2026

Risk-Aware Hierarchical Meta-Reinforcement Learning with Quantile Regression LSTM Framework for Adaptive Task Prioritization and Congestion Avoidance Offloading in Fog–Cloud Systems

A graph network with a reinforcement learning framework to avoid congestion and schedule tasks with a low makespan in fog–IoT systems and demonstrates the improved ability to ensure reliable and effective fog–cloud allocation in response to dynamically changing workloads.

Vivekananda Potti, M. R. Babu · 0 citations
#edge computing Open access Sep 2026

A Shadow's Edge Is Soft Not Because Light Bends Around It but Because the Sun Is Not a Point ── Against the Sun's angular diameter of 1919.3 arcseconds (0.533139 degrees), the penumbra widens in exact proportion to distance: 9.305029 mm at 1 m and 93.050290 mm at 10 m ── the separator is whether the gap is larger or smaller than the Sun's image ── [Paper 671]

The edge of a shadow is soft. It is sometimes said that light bends around the obstacle, but in sunlight it is not diffraction that softens the edge. Taking the Sun to be not a point but a disc 0.533139 degrees across, the softness of the edge and the shape of dappled sunlight are counted. No new theorem or law is clai...

Yuuki Yamagishi · 0 citations
#edge computing Open access Sep 2026

The Roche Limit Is Not One Distance: It Differs by a Factor of Two Depending on What Holds the Satellite Together ── in units of the planet's radius times the cube root of the density ratio, the limit is 1.259921 for a solid resisting tides alone and 2.455 for a fluid, a factor of 1.948535 apart ── the separator is whether a satellite holds its shape by fluid self-gravity, solid self-gravity or material strength ── [Paper 784]

A satellite that comes too close to its planet is torn apart by tides. That distance is called the Roche limit and is spoken of as one value. How many distances exist under the same name, by differences in what holds a satellite together, is counted. No new theorem or law is claimed. Scope of this paper (scope note): N...

Yuuki Yamagishi · 0 citations
#edge computing Open access Sep 2026

AvilaLabs/ACTINV: ACTINV 1.3.1

ACTINV v1.3.1 — release notes ACTINV 1.3.1 is a feature release centred on the measurement-driven product line: assays, facility twins, certified decision loops, and calibrated uncertainty. It also lands the resolved-resonance self-shielding quadrature — SIGMA1-broadened per temperature — plus the chance-constrained de...

Connor A · 0 citations
#edge computing Open access Sep 2026

Exploration of k-edge-deficient temporal graphs in linear time

We study the Temporal Exploration problem, where an agent must visit all vertices of a temporal graph while traversing at most one available edge per time step. Unlike static graphs, which can be explored in linear time, temporal constraints can substantially increase exploration time even when every snapshot of the gr...

Ivan Lahtin, Viktor Zamaraev · 0 citations
#edge computing Open access Sep 2026

The EBR Amplitude as a Connection Coefficient: Characterization and a Rigidity Dividing-Line Conjecture

[2026-09-23] Erratum — the logarithm at s = R. This record states that the local expansion at the dominant singularity s = R carries a logarithm arising from a resonance between the exponent −γ and the integer exponents {0, …, 2d−2}. That statement is withdrawn as an unconditional claim. The correct criterion is the on...

Papanokechi · 6 citations
#edge computing Open access Sep 2026

Finite graph certificates for composite terms in rational floor sequences

This record contains the preprint "Finite graph certificates for composite terms in rational floor sequences" by Yuri Odagiri, in English (paper-en.pdf) and Japanese (paper-ja.pdf). AbstractFor every real number ξ > 0, we give computer-assisted proofs that ⌊ξ(7/5)ⁿ⌋ is divisible by at least one of 2, 3, 5, 11, 13 for i...

Yuri Odagiri · 0 citations
#edge computing Open access Sep 2026

adelgachkar/Emergence-SDF-Vault: v30.3.8 — f_c unit convention re-registered (patch)

Release v30.3.8 — f_c unit convention re-registered (patch) Changelog from v30.3.7..HEAD (one commit): ba736d8 — f_c unit convention re-registered (E4 re-registration) The vault's registered freezing-edge constant f_c ≈ 30 THz now carries its unit convention explicitly: f_c = κ[rad/s]/π (README bullet + new note sectio...

adelgachkar · 0 citations
#federated learning Open access Sep 2026

Edge federated learning with adaptive optimization and lightweight design facilitates collaborative security situation awareness in the Industrial Internet of Things

The research provides a new security situation awareness solution with real-time, privacy and scalability for the Industrial Internet of Things, which has practical application value for collaborative security protection in complex industrial environments.

Hui-Nian He · 0 citations
#edge computing Open access Sep 2026

Project Genesis: The Unified Shadow Raven Solid-State Holographic Interactive Tactical Surface (The Smart Table Architecture) Generation One, that revolutionizes Microsoft's Smart Table.

📡 Project Metadata & Search Indexing 📄 Technical Description This repository contains the complete open-hardware engineering manifesto and architectural blueprint for CERN Open Hardware Manifesto v11.5: The Unified Solid-State Holographic Interactive Tactical Surface (The Smart Table Architecture), managed under perm...

David Michael Seagal · 0 citations
#edge computing Open access Sep 2026

How Do We Form a Safe Swarm House? From Matter to House, from House to Private Property, from Property to Distributed Intelligence — Twelve Steps of Formation, Four Tenure Invariants, Seven Safety Invariants, Forty Counterfactuals and a Runnable House

A dwelling is the smallest object that holds territory, boundary, access, exclusion, ownership, privacy, shelter, safety, services, activity, memory, identity, value, inheritance and permanence at the same moment. This article asks how such an object forms from many simple physical and computational elements, and what...

Gonçalo Melo de Magalhães · 0 citations

From tech blogs

See all →
Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.